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2nd AI Pharma Innovation: Drug Discovery
February 27 - February 28
27th – 28th February, 2019
San Francisco, USA
Brand Mission – Transforming Pharmaceutical Innovation with AI
Strapline – Optimize the Real World Application & Practical Implementation of AI & Machine Learning to Improve & Speed Up the Drug Discovery Process
As the level of pharmaceutical innovation becomes increasingly unsustainable, drug discovery processes in particular are ripe for transformational change through the application and implementation of AI and machine learning technologies. As such, the 2nd AI PI: Drug Discovery Summit 2019 returns to San Francisco to overcome data quality, data standardization and data sharing challenges in order to ensure the effective application of AI to accelerate more meaningful drug discovery.
Whether you are looking to harness the power of AI to improve target validation, lead optimisation, drug design, data mining or for drug repositioning applications, join fellow drug discovery, chemoinformatics and computational chemistry professionals as they share technical expertise and collaborate to overcome fundamental data challenges to extract maximum value of AI in a drug discovery and biological context.
Join our community and takeaway valuable insights and technical expertise to apply AI to precise and focussed areas within drug discovery to gain the maximum rewards from the continued application of AI in drug discovery.
The AI pharma summit was fantastic. The information I got was beyond exceptional. Not only did I get an overview of theories and approaches for utilizing AI in different drug discovery processes but I also got to understand the challenges facing the industry and the possible solutions. The case studies were informative and enlightening.
Sammy Cui, Senior Research Associate, Unilever
Exceptionally focused meeting joining high level strategic thinking with meaningful technical detail. Excellent slate of attendees and speakers, and in particular an amazing density of productive interstitial and after-hours networking. I’ll be very happy to attend similar meetings in the future.
Ari Allyn-Feuer, University of Michigan Medical School